“Heterogeneous” cellular networks use a mix of low-power and high-power nodes, with the low-power nodes providing smaller, localized areas of improved coverage and higher data rate service within the larger coverage areas of the high-power nodes. Such arrangements allow network operators to improve coverage and address the constantly increasing demand by users for higher data rate service, without having to incur the expense and impracticality of simply increasing the number of high-power nodes.
The coverage areas of the high-power nodes are referred to herein as “macro” cells, while the coverage areas of the low-power nodes are referred to herein as “pico” cells. These are relative terms and denote only that the pico cells generally are smaller than the macro cells. In extending this nomenclature, the high-power nodes are referred to as macro nodes and the low-power nodes are referred to as pico nodes. As such, the macro layer in a heterogeneous network comprises the macro nodes and their corresponding macro cells, while the pico layer in a heterogeneous network comprises the pico nodes and their corresponding pico cells.
Various operating schemes are known for heterogeneous networks. For example, the pico cell(s) overlaid by a given macro cell may share the same cell ID, such that the involved macro and pico node(s) operate as different transmission points within the same shared cell. In other schemes, the macro and pico nodes have unique cell IDs but may operate in cooperative fashion. For example, macro and/or pico nodes may operate in a Time Division Mode (TDM), in which they mute their transmissions according to a predetermined schedule, or “muting” pattern. This pattern of muted time periods makes it possible for communication devices and other nodes in the network to predict those time periods during which such a node will mute its transmissions and those during which it may potentially schedule transmissions. For purposes of this description, interference caused by a node that mutes its transmissions according to a particular schedule is referred to as “patterned interference.”
In one example of muting, a macro node mutes its downlink transmissions during certain times, e.g., Transmission Time Intervals or TTIs, so as not to interfere with users connected to pico nodes in or around the macro cell of the macro node. The TDM transmission pattern used for such muting comprise a predetermined allocation of timer periods that defines when the relevant macro node will refrain from scheduling transmissions to and/or from wireless communication devices served by the macro node.
Muting by a potentially interfering macro node is especially helpful for users operating in the “extended” range of a pico cell, e.g., where the coverage area of a pico node is expanded through use of a cell selection offset that improves the apparent signal quality of the pico node. However, muting is also important for pico nodes. Consider a “Home eNB” as an example pico node. Commonly, Home eNBs restrict node access using a Closed Subscriber Group (CSG) list that identifies a typically small number of wireless communication devices that are authorized to access the network through the Home eNB.
Consequently, a given wireless communication device may be operating quite close to the Home eNB and yet be unable to use it for network access. Instead, such a user would be connected to the network through the macro node. However, downlink (DL) transmissions by the serving macro node to that user may be significantly interfered with by DL transmissions by the Home eNB to its authorized users. Thus, by applying a TDM muting pattern to its DL transmissions, the Home eNB avoids interfering with nearby users connected to a macro node.
Relays represent another type of low-power node. In a known arrangement, a relay node extends or improves service within the macro cell of a macro node, which is referred to as a “donor” macro node, to indicate its support of the relay node. In an example using nomenclature from the Long Term Evolution (LTE) standard, a relay node is supported by a donor eNB, where LTE eNBs represent one type of macro node. In such contexts, a relay node uses muting times to listen to transmissions by its donor eNB.
While the use of TDM muting patterns in heterogeneous networks provides potentially significant reductions in interference for certain scheduled transmissions, it also results in potentially dramatic variations in the interference level seen by users. For example, a relay node that is close to a macro cell border generates interference with high variance to users operating in the neighbor cell(s).
Of course, a Home eNB or other pico node using muting would create similarly varying patterns of interference with respect to proximate users supported by other nodes. Further, users connected to macro nodes but operating macro cell edges may experience highly varying levels of other-cell interference arising from the patterned transmissions of neighboring macro nodes.
To avoid some of these problems, it is known, for example, for a donor eNB to provide neighboring eNBs with muting pattern information for the relay node(s) operating within the cell(s) of the donor eNB. The neighboring eNBs would use such information to avoid scheduling their cell-edge users at times when the identified relay nodes transmit or receive. However, such operation requires the sharing of such information between eNBs, adding to sidehaul signaling overhead. Further, not all cell-edge users in the neighboring macro cells are affected by the relay node(s) in question, and it is inefficient to restrict scheduling for such users in dependence on the transmit/receive times of such relay nodes.
It is also known to perform a “live,” dynamic detection of interference variance, and to incorporate the interference pattern(s) detected for a given user into ongoing scheduling decisions. For example, a wireless communication device may dynamically track the interference level it experiences, and it or the network uses such tracking to blindly detect that the device is experiencing patterned interference. In turn, the network may incorporate knowledge of the blindly detected interference pattern into the scheduling decisions made for that device, so as to avoid scheduling the device at times of high interference levels. Of course, such operation can impose significant processing and signaling burdens on individual devices and on the network at large.